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Contact detection for convex polygons/polyhedra has been a critical issue in discrete/discontinuous modelling, such as the discrete element method (DEM) and the discontinuous deformation analysis (DDA). The recently developed 3D contact theory for polyhedra in DDA depends on the so-called entrance block of two polyhedra and reduces the contact to evaluate the distance between the reference point to the corresponding entrance block, but effective implementation is still lacking.

In this paper, the equivalence of the entrance block and the Minkowski difference of two polyhedra is emphasised and two well-known Minkowski difference-based contact detection and overlap computation algorithms, GJK and expanding polytope algorithm (EPA), are chosen as the possible numerical approaches to the 3D contact theory for DDA, and also as alternatives for computing polyhedral contact features in DEM. The key algorithmic issues are outlined and their important features are highlighted.

Numerical examples indicate that the average number of updates required in GJK for polyhedral contact is around 6, and only 1 or 2 iterations are needed in EPA to find the overlap and all the relevant contact features when the overlap between polyhedra is small.

The equivalence of the entrance block in DDA and the Minkowski difference of two polyhedra is emphasised; GJK- and EPA-based contact algorithms are applied to convex polyhedra in DEM; energy conservation is guaranteed for the contact theory used; and numerical results demonstrate the effectiveness of the proposed methodologies.

This chapter develops a methodology to assist critical facility operators in designing physical protection systems to defend against a single adversary (thief, saboteur, terrorist, etc.) attack. The developed methodology utilizes a multicriteria decision-making approach that balances the competing goals of minimal security system cost and maximum system performance. The methodology utilizes a network-based approach to facility security system design and analysis, which locates physical protection (detection, delay, and response) elements throughout a facility. These elements enable the facility owner to prevent attacks through deterrence and to defeat the adversary if he or she chooses to attack. The developed approach results in the ability for the facility operator to assess relative facility and/or infrastructure safety, and make decisions regarding how to optimally allocate resources for physical protection elements to balance cost and performance. A hypothetical example is discussed which demonstrates the usefulness of the developed methodology.

The chapter considers parameter identification, estimation, and model diagnostics in medium scale DSGE models from a frequency domain perspective using the framework developed in Qu and Tkachenko (2012). The analysis uses Smets and Wouters (2007) as an illustrative example, motivated by the fact that it has become a workhorse model in the DSGE literature. For identification, in addition to checking parameter identifiability, we derive the non-identification curve to depict parameter values that yield observational equivalence, revealing which and how many parameters need to be fixed to achieve local identification. For estimation and inference, we contrast estimates obtained using the full spectrum with those using only the business cycle frequencies to find notably different parameter values and impulse response functions. A further comparison between the nonparametrically estimated and model implied spectra suggests that the business cycle based method delivers better estimates of the features that the model is intended to capture. Overall, the results suggest that the frequency domain based approach, in part due to its ability to handle subsets of frequencies, constitutes a flexible framework for studying medium scale DSGE models.

Addresses problems in mechanics and physics involving two or more coupled variables of different nature, or a number of distinct domains which interact. For these kinds of problems, considers numerical solution by the coupling of operators appertaining to the individual participating phenomena, or defined in the domains. Reviews the co‐operation of distinct discretized operators in connection with the integration of temporal evolution processes, and the iterative treatment of stationary equations of state. The specification of subtasks complies with the demand for an independent treatment on different processing units arising in parallel computation. Physical subtasks refer to problems of different field variables interacting on the continuum level; their number is usually small. Fine granularity may be achieved by separating the problem region into subdomains which communicate via the boundaries. In multiphysics simulations operators are preferably combined such that subdomains are processed in parallel on different units, while physical phenomena are processed sequentially in the subdomain.

The purpose of this paper is to develop a new and simple methodology for fabric collision detection and response.

A 3D triangle‐to‐triangle collision problem was converted to simple 2D point‐in‐triangle problem using pre‐computed 4×4 transformation matrices. The object space was partitioned using voxels to find easily collision pair triangles. k‐DOP was used to find inter‐pattern collisions.

Complex 3D collision detection problem is solved by simple matrix operations. Voxel‐based space partitioning and k‐DOP‐based hierarchical methods are successfully applied to garment simulation.

This paper shows that the collision matrix method can cover from triangle‐to‐point to triangle‐to‐triangle collision with mathematical validity and can be simply implemented in garment simulation.

This study aims to evaluate the network robustness of major Asian airlines and to explore which airport types have the greatest impact on robustness. We also analyze airports’ specific brokerage roles and their impacts on the robustness of the entire air route network. We select 10 major Asian full-service airlines that operate the main passenger terminals at the top-ranked hub airports in Asia. Data is collected from the Official Airline Guide passenger route dataset for 2017. The results of the network robustness analysis show that Air China and China Eastern Airlines have relatively high network robustness. In contrast, airlines with broader international coverage, such as Japan Airlines, Korean Air, and Singapore Airlines have higher network vulnerability. The measure of betweenness centrality has a greater impact on the robustness of air route networks than other centrality measures have. Furthermore, the brokerage role analysis shows that Chinese airports are more influential within China and Asia but are less influential globally when compared to other major hub airports in Asia. Incheon International Airport, Singapore Changi Airport, Hong Kong International Airport, and Narita International Airport play strong “liaison” roles. Among the brokerage roles, the liaison role has a greater impact on the robustness of air route networks.

This study aims to evaluate the network robustness of major Asian airlines and to explore which airport types have the greatest impact on robustness. We also analyze airports’ specific brokerage roles and their impacts on the robustness of the entire air route network. We select 10 major Asian full-service airlines that operate the main passenger terminals at the top-ranked hub airports in Asia. Data is collected from the Official Airline Guide passenger route dataset for 2017. The results of the network robustness analysis show that Air China and China Eastern Airlines have relatively high network robustness. In contrast, airlines with broader international coverage, such as Japan Airlines, Korean Air, and Singapore Airlines have higher network vulnerability. The measure of betweenness centrality has a greater impact on the robustness of air route networks than other centrality measures have. Furthermore, the brokerage role analysis shows that Chinese airports are more influential within China and Asia but are less influential globally when compared to other major hub airports in Asia. Incheon International Airport, Singapore Changi Airport, Hong Kong International Airport, and Narita International Airport play strong “liaison” roles. Among the brokerage roles, the liaison role has a greater impact on the robustness of air route networks.